Two weeks ago I wrote a First look at which teams are likely to make the 2020 NCAA hockey tournament. This article updates that with how the last two weekends’ results have changed the outlook.

Who’s a lock?

While two weeks ago there weren’t yet any mathematical guarantees, I no longer see any situation in which #1 North Dakota or #2 Minnesota State finish outside the top 10. Of course, I only search about 1,000,000 scenarios, so it might still be remotely possible (particularly if either lost out, which is so unlikely it’s still not showing up much in the scenarios).

Who’s in if they keep winning?

Two weeks ago, I identified #3 Cornell as a near lock, never dipping below #13 in the simulations. But, I did note that in the simulations Cornell never had fewer than 5 wins, so that a collapse which resulted in fewer than 5 wins in their final 12 games could push them out of contention. Cornell went 2-1-1 in the following weekends, leaving them still needing 3 more wins in their final 8 gams to be reasonably assured of being well situated going into the conference tournament.

Cornell’s situation hasn’t actually changed, Cornell is very likely to pick up the necessary wins with only two of its final eight opponents having winning records. But, as the number of games dwindles, noting how many they need to win is a bit more informative than declaring “they’re almost sure to make it”, as seemed reasonable in January.

#4 Denver is still in the position of needing to win about half of its remaining games to be sure, but will likely be in pretty good shape with just 2-3 more wins.

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Who controls their own destiny?

As is to be expected this time of year, the list of teams that control their own destiny has gotten smaller. Only down through #30 St Cloud, are pretty much assured to be on the bubble if they win out.

Also, notably, #28 Michigan Tech can no longer climb onto the bubble, even if they win out.

The following teams can put themselves on the bubble if they perform well enough:
#5 Boston College
#6 Minnesota-Duluth
#7 Clarkson
#8 Massachusetts
#9 Northeastern
#10 Arizona St
#11 Ohio St
#12 Penn St
#13 Providence
#14 Quinnipiac
#15 Maine
#16 Northern Michigan
#17 Mass.-Lowell
#18 Minnesota
#19 Bemidji St
#20 Michigan St
#21 Western Michigan
#22 Notre Dame
#23 Harvard
#24 Boston University
#25 Nebraska-Omaha
#26 New Hampshire
#27 Sacred Heart
#29 Michigan
#30 St Cloud St

Of course, the teams near the top of that list require fewer wins than do teams at the bottom. Boston College will be in good shape with 5 wins, while St Cloud St really needs 8 to be sure.

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Who needs help

Below that, only #31 Dartmouth and #35 Wisconsin show a significant chance of climbing onto the bubble if they win out. But they, like everyone else in this group, would likely need to win their conference tournament to prevent slipping back off the bubble with a season-ending loss.

The following teams should plan to win their conference tournaments if they want to make the NCAAs:
#28 Michigan Teach
#31 Dartmouth
#32 Alaska
#33 Army
#34 American International
#35 Wisconsin
#36 Bowling Gren
#37 RIT
#38 Connecticut
#39 Rensselaer
#40 Colgate
#41 Yale
#42 Colorado College
#43 Miami
#44 Holy Cross
#45 Bentley
#46 Air Force
#47 Robert Morris
#48 Lake Superior
#49 Merrimack
#50 Ferris St
#51 Canisius
#52 Union
#53 Niagara
#54 Princeton
#55 Vermont
#56 Alaska Anchorage
#57 Brown
#58 Alabama-Huntsville
#59 St. Lawrence
#60 Mercyhurst

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What’s next?

The forecasts are updated weekly, usually Monday or Tuesday, so you can always browse them yourself. I’ll also try to post interesting interpretations here, with increasing frequency as we near the end of the regular season. Meanwhile, you can explore more of the data yourself:

• PWR Rankings
• PWR Forecast

How the forecast works

The forecast page notes when the forecast was last run (assume that it includes all games that had been completed as of that time).

Each forecast is based on at least one million monte carlo simulations of the games in the described period. For each simulation, the PairWise Ranking (PWR) is calculated and the results tallied. The probabilities presented in the forecasts are the share of simulations in which a particular outcome occurred.

The outcome of each game in each simulation is determined by random draw, with the probability of victory for each team set by their relative KRACH ratings. So, if the simulation set included a contest between team A with KRACH 300 and team B with KRACH 100, team A will win the game in very close to 75% of the simulations. I don’t simulate ties or home ice advantage.